This startup is betting India’s gig economy can train the world’s robots

11:04 PM IST · May 26, 2026

In the last few years, India’sonline food delivery markethas grown significantly, with both Zomato and Swiggy going public and the number of cloud kitchens increasing. Meanwhile, startups working on home services, such as on-demand household staffing platforms like Urban Company,Snabbit, andPronto, have gained popularity. Silicon Valley-based startupHuman Archiveis tapping into this trend, partnering with these companies to have workers wear special caps with cameras to collect egocentric (first-person point of view) video data of everyday tasks that could be used to train robots. Without naming specific partners, the startup said it is working with companies in the home services, hotel, and restaurant sectors to collect egocentric data, and it says it has more than 1,000 active headsets deployed across multiple locations. On the back of that traction, Human Archive said Tuesday it has raised $8.2 million in funding from Wing Venture Capital, NVP Capital, Y Combinator, and angels from OpenAI, Nvidia, Google, Mercor, AfterQuery, BAIR, SAIL, Brad Boa, and Meta. The startup was founded by three students from UC Berkeley and one from Stanford — Samay Maini, Rushil Agarwal, Shloke Patel, and Raj Patel, the latter two being cousins. (Raj Patel is CEO.) All four have research backgrounds spanning robotics, hardware, and tactile data. The company’s founding is a direct bet on where the AI industry is heading. As robotics labs and frontier AI companies race to build machines that can perform physical tasks in the real world, they face a critical bottleneck — a shortage of high-quality, real-world training data showing humans doing everyday work. Human Archive’s bet is that the workers staffing India’s booming gig economy represent an untapped and scalable source of exactly that data. While Human Archive is working with multiple partners, the startup said it was rejected by many Indian home services companies, including Pronto and Urban Company, for a collaboration. The company’s rejection by major players became public fodder last weekend, when Indian outlet Entrackrreportedthat Pronto is actively seeking partnerships to collect worker data for robotics training and that Snabbit had held early discussions with Human Archive before the project fell apart. Urban Company CEO Abhiraj Singh Bhalrespondedon X, stating the company would not engage in such arrangements — prompting Patel tofire backthat Urban Company would soon be forced to reconsider or risk losing relevance to customer churn. Co-founder Rushil Agarwal was blunter still, posting that Pronto founder Anjali Sardana hadlaughedat him and called him “stupid” when he raised the idea of a data partnership. Pronto acknowledged the conversations but said it chose not to move forward. Across the country, other startups are collecting egocentric data fromdifferent work environments, including factory floors. To differentiate itself, Human Archive is using and developing additional devices, such as tactile gloves, a full-body motion capture suit, and wrist cameras to capture data, including motion and tactile force, synchronously aligned with RGB-D (color imagery paired in real time with depth information), to sell to AI labs. The startup believes that video data alone is not sufficient but that pairing it with other sensor data makes it much more valuable. Initially, Human Archive used makeshift setups or off-the-shelf rigs to capture the data. Now it is working on custom hardware that works together and captures different kinds of data. It already has more than 50 different devices deployed to collect different data points. “To capture data, we started with iPhones; then we built our own custom rigs and caps. Now we have more than seven different hardware products that we use interchangeably across different modalities. After data collection from different devices, we worked on synchronizing data from all these different sources,” Patel said in a call. The company said it is developing ways to fine-tune AI models with its own data and test them on robots to evaluate task effectiveness. By doing this, the startup can demonstrate the quality of its data to potential customers and post-train internal models. Zach DeWitt, a partner at Wing VC, said the startup has a unique advantage in collecting data from multiple sensors. “No one else in the world has been able to synchronize and collect headset RGB-D, force feedback, full-body motion capture, and synchronized chest and wrist camera data at scale. They’ve been doing internal model training on this data, and every major lab and university is interested in running experiments on it due to the novelty of the sensors and the scale of the new dataset they are releasing soon,” he told TechCrunch. Despite rejection from notable players in the home services industry, Human Archive teamed up with smaller startups to offer discounted services to customers. When a worker arrives at a home, consumers are offered a choice through the app: pay a discounted price in exchange for consenting to data collection, or pay the full price for an unrecorded visit. Patel mentioned that customers have been happy to opt for the former, as disputes about service quality are common, and video recordings can help resolve them. The company pays workers a base rate of $1 per hour for participating in egocentric data collection. A report from the Economic Times suggests that other companies pay ₹250 to ₹400 per hour (roughly $2.63 to $4.20). Patel said competitors pay more than Human Archive, but its on-the-ground presence in India allows it to keep compensation lower. “Human Archive’s network provides immediate, flexible earning opportunities globally, lowering the barrier to participating in the AI economy. We see this as a critical bridge that funds immediate livelihoods while building the infrastructure for a safer, more productive future,” DeWitt said. Beyond wage payment, there are privacy concerns around data collection via video recording. It is not clear what information Human Archive gives workers about how their footage is used. The company said that its commercial contracts are compliant with India’sDigital Personal Data Protection (DPDP) Act, as it displays a privacy policy notice, along with consent information detailing the purpose of data collection and how it is processed. The company said all data is anonymized and faces are blurred from recordings. Last week, Moneycontrolreportedthat India’s Ministry of Electronics and Information Technology is looking into the consent mechanisms and data-collection practices of startups collecting egocentric data through home service workers. While Human Archive largely collects data in India, it has started expanding into Southeast Asia and the U.S. The company is also building a platform for anyone to participate in data collection and earn money. It also wants to offer customers in the U.S. services like cleaning or cooking in exchange for data collection by participating workers — though these programs are just in an early pilot stage. Multiple well-funded startups areracingto buildphysical AI. Doing so requires massive amounts of training data showing humans at work — and Human Archive is one of the players competing to serve that demand. Whether its approach can scale will hinge on the partnerships it strikes and the uniqueness and volume of the data it can collect to satisfy the appetite of physical AI labs.

Latest AI News

View All News →

Nobel-Winning AlphaFold Scientist John Jumper Leaves Google DeepMind for Anthropic

For his work on AlphaFold, Jumper shared the 2024 Nobel Prize in Chemistry with Demis Hassabis and scientist David Baker.

1 hour ago

View

How Hexaware's GIFT City Move Gives Indian IT a New Financial Frontier

Hexaware plans to create nearly 1,000 high-skilled jobs over the next three years.

5 hours ago

View

Encryption, spyware, and now Mythos: History shows why cyber export control doesn’t work

Last Friday, citing unspecified national security concerns, the White Houseordered Anthropicto restrict the export of its powerful AI models Fable and Mythos to anyone outside of the United States, as well as foreign nationals inside the country. Shortly after, the AI giant hastily pulled the plug on both models, which have now been unavailable to anyone for a week. The episode is the first real test of whether the U.S. government can use export controls to contain frontier AI the way it has tried, with very uneven results, to contain encryption and spyware before it. And dramatic as it may sound, how this standoff gets resolved could shape not just Anthropic’s access to foreign markets but the rulebook that other AI labs will have to build around. Some context first.Ever since Anthropic launched Mythos in April, the company has marketed it assome kind of Doomsday cyber machinethat could wreak havoc on the internet if released too widely — which is why, before the ban,only around 150 vetted companies and government organizationshad access to it at all. The goal was helping defenders secure their software and services before the bad guys could reach Mythos-like capabilities. So what triggered the ban? Two subsequent events, reportedly. The first: Anthropic gave a South Korean telecom access to Mythos through its limited partner program, and U.S. officials grew alarmed after identifying the company as one they suspected had ties to China. (The company,widely reportedto be SK Telecom, hasdeniedany China connection.) Amazon CEO Andy Jassy also reportedlyalerted the administrationafter Amazon’s own researchers, he said, found a way around Fable 5’s safeguards. Anthropic disputes the “jailbreak” label, calling it a narrow, already-patched issue rather than a wholesale defeat of the model’s safety measures. The result was the same: the Commerce Department issued an export control directive, and Anthropic had to scramble to immediately limit access to its products — within roughly 90 minutes of being notified, by some accounts. None of this is new, though. Governments have tried to use export controls to limit the proliferation of what they see as dangerous cyber technology for decades, but their track record has been middling at best. The U.S. government was behind what is perhaps history’s most spectacular failure of this approach in the early to mid-1990s. At the time, computer scientists were developing encryption technologies to secure data as it traveled over the internet. One of those encryption products was called Pretty Good Privacy, or PGP, a popular software that could encrypt data and make it virtually impossible to unscramble even if intercepted as it traveled to its intended recipient over the internet. The U.S. government initially saw PGP as a dangerous weapon, fearing it would prevent its intelligence agencies from snooping on emails as they crossed their wires. To stop the distribution of PGP, the U.S. Customs Serviceopened a criminal investigationagainst PGP’s creator Phil Zimmermann for allegedly violating arms export controls. He fought back by publishing PGP’s source codeas a printed book, igniting what is known today as the “Crypto Wars.” Zimmermann later won a key battle when the investigation was closed, paving the way for crucial end-to-end encryption algorithms such as the one used by billions of Signal and WhatsApp users. Later during the early 2010s, researchers began discovering Western-made spyware used against dissidents in the Middle East. In response, several governments agreed to expandthe Wassenaar Arrangement, an international treaty that limits the export of dual-use software and technologies that are used in both civilian and military applications. The idea was to classify surveillance and hacking software as dual-use, thus forcing spyware makers to get export licenses to sell their products abroad. Contact UsDo you have more information about the Mythos ban? From a non-work device and network, you can contact Lorenzo Franceschi-Bicchierai securely on Signal at +1 917 257 1382, or via Telegram and Keybase @lorenzofb, oremail. But Wassenaar has always had two inherent weaknesses. There are several countries that don’t adhere to the agreement, including Israel, which houses some of the world’s most active spyware makers. The agreement also depends on countries applying it to companies within their borders at their own discretion. For a time, the Italian government allowed one of the country’s then-top spyware makers, Hacking Team, a license to export its tools around the world, despite the company’s track record of selling spyware tooppressivegovernmentsthatused itto hack journalists and human rights activists. Since then,othercountriesin Europe have been lax with spyware makers like Italy. Despite numerous scandals, Europe, home tomany spyware and hacking tools makers, hascontinually failed to curb the export of spywareto authoritarian regimes. Critics say that a recently renewed effort across the bloc of 27 member states to tackle its growing problem of spyware exports to authoritarian states “does not go far enough.” Several spyware makers, such as Intellexa, a sanctioned consortium of spyware companies, have simply moved their operations to countries with lax export controls. Other spyware makers sought to move their operations to Saudi Arabia for similar reasons. There have been some wins. Germany-based spyware maker FinFishershut down in 2022after a multi-year investigation by German prosecutors into the company forallegedly selling spywareto Turkey without an export license. Investigators previously found the FinFisher spyware had beendeployed on the phonesof critics of Turkey’s government. As of the time of writing, the impasse between Anthropic and the Trump administration remains. There is a reasonable chance the administration will buckle and lift the restriction in the interest of keeping American AI companies competitive worldwide — a move that would amount to tacit acknowledgment that AI labs elsewhere, including in China, will likely reach similar capabilities regardless of what the U.S. restricts. Or, American AI companies could end up needing government approval before serving foreign customers at all, a compliance burden that would invariably dent their bottom line. Given the past experiences that world governments have had with trying to control the reach of software, government-mandated export controls are unlikely to be the right approach to stop malicious actors from abusing powerful dual-use cyber technologies.

9 hours ago

View

Billionaire Ambani wants AI in every call, app, and home

As India searches for a homegrown contender in the global artificial intelligence race, billionaire Mukesh Ambani is positioning Reliance Industries as a national champion, rolling out AI services for phone calls, mobile apps, and connected homes. At itsannual shareholder meetingon Friday, the Mumbai-based conglomerate announced Jio Call Agent, an AI assistant that can join phone calls to transcribe conversations, generate summaries, and perform tasks such as booking cabs, ordering food, and making reservations. The service, which can be activated by saying “Hey Jio,” is expected to launch later this year for Jio’s more than 500 million users. By embedding the service directly into its telecom network rather than offering it as a stand-alone app, Jio is betting AI assistance can become a native feature of phone calls. The approach could reduce consumers’ reliance on third-party call-assistant apps and give Reliance a powerful distribution advantage in an increasingly crowded AI market. Reliance also unveiled an AI-powered version of its MyJio app that can perform tasks on behalf of users, from activating eSIMs to selecting roaming plans, through natural-language requests. The company further introduced TeleFrame, a home display that uses AI agents to proactively surface information and recommendations, such as weather alerts, schedules, and household reminders. The product appears to echo a broader industry push toward ambient AI assistants for the home, an area being explored by companies such asAmazonandGoogle. The announcements mark the next phase of Reliance’s AI ambitions as India seeks to build domestic capabilities in a field largely dominated by U.S. and Chinese technology companies. The push follows thelaunch of Reliance Intelligencelast year, through which the conglomerate aims to develop AI infrastructure and services for consumers, businesses, and governments, including applications that support 22 Indian languages. “India should not be a mere consumer of AI created elsewhere. It must become a creator, adopter, and a global leader in AI,” Ambani, age 69, said. Reliance has been ramping up its AI ambitions through partnerships withGoogle,Meta, andNvidia. Earlier this year, the company announced plans toinvest $110 billion in AI infrastructureas it seeks to establish itself as a major player in India’s emerging AI ecosystem. At the shareholder meeting, Reliance also unveiled a suite of AI services for healthcare, education, agriculture, and small businesses. The products, branded JioHealthIQ, JioLearnIQ, JioKrishiIQ, and AI Vyapar, are designed to operate across multiple Indian languages and cater to local needs, the company said. The shareholder meeting also brought a major development for investorsawaiting Jio’s stock market debut. Ambani said Jio Platforms’ board had approved a draft prospectus for an initial public offering that would include a fresh issue of up to 270 million shares, according to a stock exchange filing. The announcements also raise questions about how Reliance will handle user data as it expands AI services across phone calls, mobile apps, and connected homes. While the company said the services would operate with user consent, it did not answer questions about whether data generated through the products could be used to train AI models or shared with technology partners. Reliance’s AI ambitions come as Indian companies remain heavily reliant on foreign AI models and cloud providers.Recent restrictions on accessto some of Anthropic’s latest models have underscored that dependency, showing how decisions made overseas can affectstartups and businessesbuilding AI products in India — the kind of supply-chain risk that’s pushing Indian conglomerates toward building their own stack rather than renting someone else’s. Last week, Reliance announced acollaboration with Meta to establish an AI data centerin the western state of Gujarat, building on Meta’s earlier investment in Jio Platforms and a joint venture launched last year to develop AI solutions for enterprise customers in India and overseas markets. Reliance is not alone in pursuing AI opportunities.Tata Consultancy Services,Infosys, and rivalAdani Grouphave also expanded their AI initiatives and partnerships with global players, including Anthropic, Google, and OpenAI, as India’s largest corporations race to secure a leading role in the country’s AI future. Nonetheless, for Reliance, the stakes are particularly high; it’s preparing Jio for a long-awaited stock market debut and needs new growth drivers, with the conglomerate’s shares down about 17% this year.

17 hours ago

View

Quick Links

AI Tools by Task

Alternatives

Best AI Tools

Top AI Tools

Browse & Compare

AI Insights

Submit your Tool

Submit AI Tools – The ultimate platform to discover, submit, and explore the best AI tools across various categories.

PoweredByAI.app is an AI Tools Directory helping individuals, businesses, and creators discover the best AI tools for writing, coding, design, productivity, and more.

Contact Promote Analytics Terms of Service Refund Policy Privacy Policy